This book is intended for those who want to learn how to use R's capabilities to build models in quantitative finance at a more advanced level. If you wish to perfectly take up the rhythm of the chapters, you need to be at an intermediate level in quantitative finance and you also need to have a reasonable knowledge of R.
What you will learn
Analyze high frequency financial data
Build, calibrate, test, and implement theoretical models such as cointegration, VAR, GARCH, APT, BlackScholes, Margrabe, logoptimal portfolios, coreperiphery, and contagion
Solve practical, realworld financial problems in R related to big data, discrete hedging, transaction costs, and more.
Discover simulation techniques and apply them to situations where analytical formulas are not available
Create a winning arbitrage, speculation, or hedging strategy customized to your risk preferences
Understand relationships between market factors and their impact on your portfolio
Assess the tradeoff between accuracy and the cost of your trading strategy